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Cours associés (13)

FIN-407: Machine learning in finance

This course aims to give an introduction to the application of machine learning to finance, focusing on the problems of portfolio optimization, return prediction, and textual analysis. A particular focus will be on deep learning and the practical details o ...

EE-568: Reinforcement learning

This course describes theory and methods for Reinforcement Learning (RL), which revolves around decision making under uncertainty. The course covers classic algorithms in RL as well as recent algorithms under the lens of contemporary optimization. ...

EE-451: Image analysis and pattern recognition

This course gives an introduction to the main methods of image analysis and pattern recognition. ...

MICRO-455: Machine learning I

MATH-520: Topics in machine learning

Mathematical analysis of modern supervised machine learning techniques, with an emphasis on the mathematics of artificial neural networks. ...

CS-330: Intelligence artificielle

Introduction aux techniques de l'Intelligence Artificielle, complémentée par des exercices de programmation qui montrent les algorithmes et des exemples de leur application à des problèmes pratiques. ...

EE-566: Adaptation and learning

In this course, students learn to design and master algorithms and core concepts related to inference and learning from data and the foundations of adaptation and learning theories with applications.

ME-390: Foundations of artificial intelligence

This course provides the students with 1) a set of theoretical concepts to understand the machine learning approach; and 2) a subset of the tools to use this approach for problems arising in mechanical engineering applications. ...

MGT-448: Statistical inference and machine learning

This course aims to provide graduate students a thorough grounding in the methods, theory, mathematics and algorithms needed to do research and applications in machine learning. The course covers topics from machine learning, classical statistics, and data ...

EE-806: Multi Agent Reinforcement Learning

The goal of the summer school are providing a rigorous introduction to the foundations of MARL and highlight the challenges that arise in the modern research directions in this area. ...

EE-618: Theory and Methods for Reinforcement Learning

This course describes theory and methods for decision making under uncertainty under partial feedback. ...

MGT-644(b): Computational Methods for Doctoral Research in Management

The objective of this course is to introduce doctoral students to computational methods for data-driven empirical research in management. ...

CS-434: Unsupervised & reinforcement learning in neural networks

Learning is observable in animal and human behavior, but learning is also a topic of computer science. This course links algorithms from machine learning with biological phenomena of synaptic plasticity. The course covers unsupervised and reinforcement le ...